Khushbu Shah

1 week ago | medium.com | Khushbu Shah

“What if your AI could pull the perfect answer from the world’s knowledge every single time?”Retrieval-augmented generation (RAG) is the quiet revolution behind today's best-performing AI systems. ChatGPT’s ability to cite sources and enterprise AI’s scanning of thousands of documents highlight the need for grounding language models in reality, a role fulfilled by Retrieval-Augmented Generation (RAG). But here’s the catch: RAG isn’t one-size-fits-all.

3 weeks ago | medium.com | Khushbu Shah

Have you ever wondered how AI agents can go from simple chatbots to complex collaborators managing entire workflows? All thanks to rapid advances in reasoning, multimodal capabilities, and tool integration, Large Language Models (LLMs) are evolving beyond single-task tools. Today, they can act as agents — autonomous systems that don’t just assist but take over tasks, coordinate actions, and make real-time decisions.

1 month ago | medium.com | Khushbu Shah

If you’ve ever used a voice assistant like Siri, Alexa, or Google Assistant, you’ve already witnessed the magic of conversational AI. But have you ever wondered how these systems understand and respond like a human? That’s where models like Sesame’s Conversational Speech Model (CSM) come into play. In this blog, we’ll break down what Sesame’s CSM is, how it works, what makes it stand out, and how you can use it to build your own speech-based AI applications.

1 month ago | eater.com | Khushbu Shah

They say the eyes eat first, but before we even see what we are eating, we often enjoy its aroma. The scent of a beloved dish, such as the gooey chocolate chip cookies your mom would pull out of the oven after school or the malty almond granita you had for breakfast while on vacation in Sicily, can evoke feelings of pleasure, happiness, and nostalgia. So it’s no surprise that gourmand perfumes and fragrances inspired by the edible world have skyrocketed in popularity.

1 month ago | medium.com | Khushbu Shah

Khushbu Shah·FollowPublished inProjectPro·7 min read·--80% of AI projects fail — not because of bad models but because of bad architecture. Before you build and train an AI model, deploy an AI agent, or ship an AI application, there is one question that will shape everything: Single Agent vs Multi Agent in AI. This isn’t just a technical choice. It’s a strategic fork determining whether your AI project will scale or stall.